arXiv subjects

Oriol Sallent

Publications and source records attributed to Oriol Sallent.

7 recordsLinked to original sources

arXiv2026

Toward Fully Autonomous 6G Networks: AI-driven Operational Efficiency and Optimization

Mobile networks evolution is characterized by a substantial increase in system complexity, driven by the need to accommodate a growing number of heterogeneous services on top of the digital infrastructure. This growth in service accommodation is expected to accelerate with the adoption of the Network as a Service (NaaS) paradigm, which has emerged as a promising approach to accelerate network innovation while enabling new revenue streams for operators. Although it is fundamental to abstract network capabilities for third-party developers, it poses significant challenges in terms of efficient network operation. To address this increased complexity, future mobile networks are envisioned to be inherently Artificial Intelligence (AI)-native. In particular, the integration of AI within the Radio Access Network (RAN) becomes a key enabler for optimizing operation, energy consumption, and autonomous network control. In this context, this research explores the convergence of AI-native RAN and NaaS ecosystems to enable autonomous 6G RAN management. We propose an Agentic-based orchestration framework capable of interpreting intent-based policies. The proposed framework becomes key to integrate external NaaS requests with internal network management policies.

cs.NI↗

arXiv2026

A Practical AI-Driven Strategy for Cell On/Off Switching under Adaptable QoS Constraints

The rapid expansion of 5G networks has intensified concerns over their sustainability, as denser Radio Access Network (RAN) deployments have increased overall power consumption. Although numerous studies have examined energy-efficient cell on/off switching, few have focused on approaches capable of dynamically adapting to operator-defined Quality of Service (QoS) requirements. In this paper, we propose a Long Short Term Memory (LSTM)based strategy, trained using a dataset from a European Mobile Network Operator (MNO), that enforces both target throughput levels and outage-tolerance constraints. Unlike previous approaches, our model adapts to different QoS requirements by tuning a decision threshold at inference time, enabling operators to balance energy savings and service guarantees without retraining. Across an unseen week, the method attains 63 to 96 % of an oracle's energy savings while largely meeting operator-specified constraints. We also provide CO2 and OPEX estimates under representative scenarios to quantify potential operator benefits.

cs.NI↗

arXiv2024

Low Layer Functional Split Management in 5G and Beyond: Architecture and Self-adaptation

Radio Access Network (RAN) disaggregation is emerging as a key trend in beyond 5G, as it offers new opportunities for more flexible deployments and intelligent network management. A relevant problem in disaggregated RAN is the functional split selection, which dynamically decides which baseband (BB) functions of a base station are kept close to the radio units and which ones are centralized. In this context, this paper firstly presents an architectural framework for supporting this concept relying on the O-RAN architecture. Then, the paper analyzes how the functional split can be optimized to adapt to the different load conditions while minimizing energy costs.

cs.NI↗

arXiv2022

On the Implementation of a Reinforcement Learning-based Capacity Sharing Algorithm in O-RAN

The capacity sharing problem in Radio Access Network (RAN) slicing deals with the distribution of the capacity available in each RAN node among various RAN slices to satisfy their traffic demands and efficiently use the radio resources. While several capacity sharing algorithmic solutions have been proposed in the literature, their practical implementation still remains as a gap. In this paper, the implementation of a Reinforcement Learning-based capacity sharing algorithm over the O-RAN architecture is discussed, providing insights into the operation of the involved interfaces and the containerization of the solution. Moreover, the description of the testbed implemented to validate the solution is included and some performance and validation results are presented.

cs.NI↗

arXiv2021

Self-Dimensioning and Planning of Small Cell Capacity in Multitenant 5G Networks

An important concept in the fifth generation of mobile networks is multitenancy, which allows diverse operators sharing the same wireless infrastructure. To support this feature in conjunction with the challenging performance requirements of future networks, more automated and faster planning of the required radio capacity is needed. Likewise, installing small cells is an effective resource to provide greater performance and capacity to both indoor and outdoor places. This paper proposes a new framework for automated cell planning in multitenant small cell networks. In particular, taking advantage of the available network data, a set of detailed planning specifications over time and space domains are generated in order to meet the contracted capacity by each tenant. Then, the network infrastructure and configuration are updated according to an algorithm that considers different actions such as adding/removing channels and adding or relocating small cells. The simulation results show the effectiveness of various methods to derive the planning specifications depending on the correlation between the tenant's and network's traffic demands.

cs.NI↗

arXiv2021

Capacity Self-Planning in Small Cell Multi-Tenant 5G Networks

Multi-tenancy allows diverse agents sharing the infrastructure in the 5 th generation of mobile networks. Such a feature calls for more automated and faster planning procedures in order to adapt the network capacity to the varying traffic demand. To achieve these goals, Small Cells offer network providers more flexible, scalable, and cost-effective solutions compared to macrocell deployments. This paper proposes a novel framework for cell planning in multi-tenant Small Cell networks. In this framework, the tenant's contracted capacity is translated to a set of detailed planning specifications over time and space domains in order to efficiently update the network infrastructure and configuration. Based on this, an algorithm is proposed that considers different actions such as adding/removing channels and adding or relocating small cells. The proposed approach is evaluated considering the deployment of a new tenant, where different sets of planning specifications are tested.

cs.NI↗

arXiv2015

A Prioritised Traffic Embedding Mechanism enabling a Public Safety Virtual Operator

Public Protection and Distaster Relief (PPDR) services can benefit greatly from the availability of mobile broadband communications in disaster and emergency scenarios. While undoubtedly offering full control and reliability, dedicated networks for PPDR have resulted in high operating costs and a lack of innovation in comparison to the commercial domain. Driven by the many benefits of broadband communications, PPDR operators are increasingly interested in adopting mainstream commercial technologies such as Long Term Evolution (LTE) in favour of expensive, dedicated narrow-band networks. In addition, the emergence of virtualization for wireless networks offers a new model for sharing infrastructure between several operators in a flexible and customizable manner. In this context, we propose a virtual Public Safety (PS) operator that relies on shared infrastructure of commercial LTE networks to deliver services to its users. We compare several methods of allocating spectrum resources between virtual operators at peak times and examine how this influences differing traffic services. We show that it is possible to provide services to the PS users reliably during both normal and emergency operation, and examine the impact on the commercial operators.

cs.NI↗